main : main title
pseudoimage <- image(raw_data, transfo=log2)
MA_plot <- MAplot(raw_data)
## Warning in KernSmooth::bkde2D(x, bandwidth = bandwidth, gridsize = nbin, :
## Binning grid too coarse for current (small) bandwidth: consider increasing
## 'gridsize'
## Warning in KernSmooth::bkde2D(x, bandwidth = bandwidth, gridsize = nbin, :
## Binning grid too coarse for current (small) bandwidth: consider increasing
## 'gridsize'
### QA: Statistics
# BiocManager::install("AnnotationDbi")
# BiocManager::install("Biobase")
IQRray
# The IQRray statistic is obtained by ranking all the probe intensities from
# a given array and by computing the average rank for each probe set. The
# interquartile range (IQR) of the probe sets average ranks serves then as
# quality score.
#Example of a low score: 122783.6
# high score: 226124.6
library(methods)
library(AnnotationDbi)
library(Biobase)
#data - Affybatch object obtained after reading in celfiles into R with function ReadAffy from package affy
#obtaining intensity values for perfect match (pm) probes
pm_data<-pm(raw_data)
#ranking probe intensities for every array
rank_data<-apply(pm_data,2,rank)
#obtaining names of probeset for every probe
probeNames<-probeNames(raw_data)
#function computing IQR of mean probe ranks in probesets
get_IQR<-function(rank_data,probeNames){round(IQR(sapply(split(rank_data,probeNames),mean)),digits=2)}
#computing arIQR score
IQRray_score<-apply(rank_data,2,get_IQR,probeNames=probeNames)
Normalize Data
#rma (Robust Multiarray Averaging)
#plm (Probe Level Models)
#normalized_data <- rma(raw_data, background=TRUE, normalize=TRUE, subset=NULL)
norm_probe <- normalize(raw_data)
## Normalizing... OK
norm_probe_table <- exprs(norm_probe)
#row names : genes
#column names : samples
norm_gene <- rma(raw_data)
## Background correcting
## Normalizing
## Calculating Expression
norm_gene_table <- exprs(norm_gene)
#probe_level <- fitProbeLevelModel(raw_data, background=TRUE, normalize=TRUE, target="core", method="plm", verbose=TRUE, S4 = FALSE)
raw_table <- exprs(raw_data)
Verify Normalization
print("Verify Normalization step")
## [1] "Verify Normalization step"
DGE Analysis
print("DGE Analysis step")
## [1] "DGE Analysis step"
Gene Annotations
print("Gene Annotations step")
## [1] "Gene Annotations step"